code: def testAggregationMethod(self):
      for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
          with self.cached_session():
              var0 = variables.Variable([1.0, 2.0], dtype=dtype)
              var1 = variables.Variable([3.0, 4.0], dtype=dtype)
              cost = 5 * var0 + 3 * var1
              global_step = variables.Variable(
                  array_ops.zeros([], dtypes.int64), name="global_step"
              )
              sgd_op = gradient_descent.GradientDescentOptimizer(3.0)
              opt_op = sgd_op.minimize(
                  cost,
                  global_step,
                  [var0, var1],
                  aggregation_method=gradients_util.AggregationMethod.EXPERIMENTAL_ACCUMULATE_N,
              )
  
              self.evaluate(variables.global_variables_initializer())
              # Fetch params to validate initial values
              self.assertAllClose([1.0, 2.0], self.evaluate(var0))
              self.assertAllClose([3.0, 4.0], self.evaluate(var1))
              # Run 1 step of sgd through optimizer
              opt_op.run()
              # Validate updated params
              self.assertAllClose([-14.0, -13.0], self.evaluate(var0))
              self.assertAllClose([-6.0, -5.0], self.evaluate(var1))
  
imports: from tensorflow.python.distribute import cross_device_ops
  from tensorflow.python.distribute import distribute_utils
  from tensorflow.python.distribute import mirrored_strategy
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import clip_ops
  from tensorflow.python.ops import gradients_util
  from tensorflow.python.ops import resource_variable_ops
  from tensorflow.python.ops import state_ops
  from tensorflow.python.ops import variables
  from tensorflow.python.platform import test
  from tensorflow.python.training import adam
  from tensorflow.python.training import gradient_descent
label_desc: Use image node_id 2 for calling the OptimizerTest obj's underlying member method code with example usage: obj.testAggregationMethod() without return types